Method, system and computer program product for interactively identifying same individuals or objects present in video recordings

ABSTRACT

A method, system and computer program product for interactively identifying same individuals or objects present in video recordings is disclosed. When a thumbnail in a set of thumbnails is selected, new information is obtained. The new information may be that an individual or object is present in the portion of the video recording associated with the thumbnail. A search can be carried out for the individual or object based on the new information. The search generates new match likelihoods for each of displayed thumbnails within a user interface page. The displayed thumbnails are re-ordered based on the new match likelihoods.

RELATED U.S. APPLICATION DATA

The present application is a continuation of U.S. patent applicationSer. No. 16/160,882, filed on Oct. 15, 2018, which is a divisional ofU.S. patent application Ser. No. 15/368,357 (now issued as U.S. Pat. No.10,121,515), filed on Dec. 2, 2016, which claims the benefit of priorityof: i) provisional application No. 62/346,240 filed on Jun. 6, 2016; andii) provisional application No. 62/351,806 filed on Jun. 17, 2016. Thecontents of all of the above-mentioned applications are herebyincorporated by reference in their entireties.

FIELD

The present subject-matter relates to identifying same individuals orobjects appearing in a plurality of different video recordings and, inparticular, to allowing a user to provide input into a computer terminalof a surveillance system in order to facilitate identifying sameindividuals or objects appearing in a plurality of different videorecordings.

BACKGROUND

Intelligent processing and playback of recorded video is an importantfunctionality to have in camera surveillance systems. The playback ofrecorded video may be useful to review and identify objects or personsof interest found in the video captured by the cameras. This may then beused for some security-related purpose or purpose such as, for example,locating the object or person of interest.

However, camera surveillance systems may have a large number of camerasthat are each generating their own respective video feed. This may makethe simultaneous review of these feeds during playback cumbersome, timeconsuming and expensive.

SUMMARY

According to one example embodiment, there is provided a method thatincludes displaying a plurality of sets of thumbnails. Each set ofthumbnails includes one or more thumbnails positioned in a respectiverow or column which, along with the set of thumbnails, are defined by aunique time interval of a plurality of time intervals. Each thumbnail ofeach set of thumbnails is visually representative of an associatedportion of a video recording taken at the defined time interval for thethumbnail. The one or more thumbnails in each set of thumbnails areorganized in a descending order arrangement starting at one end of therespective row or column with a thumbnail corresponding to a highestlikelihood, as compared to any other thumbnails of the set, ofappearance of an individual or object having been identified as being ofinterest. Any remaining thumbnails in the set are displayed, indescending order, extending away from the thumbnail corresponding to thehighest likelihood. The method also includes allowing selection of afirst thumbnail in one of the sets of thumbnails to obtain newinformation that the individual or object is present in the portion ofthe video recording associated with the first thumbnail. The method alsoincludes carrying out a search for the individual or object based on thenew information, and the search generates new match likelihoods for eachof the displayed thumbnails. The method also includes re-ordering thedisplayed thumbnails based on the new match likelihoods so as tomaintain the descending order arrangement in each of the sets ofthumbnails.

According to another example embodiment, there is provided a tangible,non-transitory, computer-readable storage medium having instructionsencoded therein, wherein the instructions, when executed by at least oneprocessor, cause a carrying out of a method that includes displaying aplurality of sets of thumbnails. Each set of thumbnails includes one ormore thumbnails positioned in a respective row or column which, alongwith the set of thumbnails, are defined by a unique time interval of aplurality of time intervals. Each thumbnail of each set of thumbnails isvisually representative of an associated portion of a video recordingtaken at the defined time interval for the thumbnail. The one or morethumbnails in each set of thumbnails are organized in a descending orderarrangement starting at one end of the respective row or column with athumbnail corresponding to a highest likelihood, as compared to anyother thumbnails of the set, of appearance of an individual or objecthaving been identified as being of interest. Any remaining thumbnails inthe set are displayed, in descending order, extending away from thethumbnail corresponding to the highest likelihood. The method to becarried out by the instructions encoded in the storage medium alsoincludes allowing selection of a first thumbnail in one of the sets ofthumbnails to obtain new information that the individual or object ispresent in the portion of the video recording associated with the firstthumbnail. The method to be carried out by the instructions encoded inthe storage medium also includes sending a request to a server to searchfor the individual or object based on the new information. The searchgenerates new match likelihoods for each of the displayed thumbnails.The method to be carried out by the instructions encoded in the storagemedium also includes re-ordering the displayed thumbnails based on thenew match likelihoods so as to maintain the descending order arrangementin each of the sets of thumbnails.

According to another example embodiment, there is provided a method thatincludes providing a user interface which includes a video player fordisplaying video frames of a video. The video frames include a number offrame regions within which there are respective moving bodies of matter.The frame regions are selectable for receiving user input. The methodalso includes receiving search-requesting input through the userinterface to carry out a search for an individual or object present in aselected frame region of the frame regions. The method also includesgenerating or re-computing a plurality of match likelihoods assigned toa plurality of individuals or objects present in video recordings. Thematch likelihoods are likelihoods of there being an appearance of theindividual or object. The method also includes populating or updating auser interface page of the user interface to display informationcorresponding to the generated or re-computed match likelihoods.

According to another example embodiment, there is provided a tangible,non-transitory, computer-readable storage medium having instructionsencoded therein, wherein the instructions, when executed by at least oneprocessor, cause a carrying out of a method that includes providing auser interface which includes a video player for displaying video framesof a video. The video frames include a number of frame regions withinwhich there are respective moving bodies of matter. The frame regionsare selectable for receiving user input. The method to be carried out bythe instructions encoded in the storage medium also includes receivingsearch-requesting input through the user interface to carry out a searchfor an individual or object present in a selected frame region of theframe regions. The method to be carried out by the instructions encodedin the storage medium also includes sending a request to a server togenerate or re-compute a plurality of match likelihoods assigned to aplurality of individuals or objects present in video recordings. Thematch likelihoods are likelihoods of there being an appearance of theindividual or object. The method to be carried out by the instructionsencoded in the storage medium also includes populating or updating auser interface page of the user interface to display informationcorresponding to the generated or re-computed match likelihoods.

According to another example embodiment, there is provided a method thatincludes displaying a two dimensional graph having date and time alongthe x-axis and, along the y-axis, a listing of a plurality of cameraidentifications of video cameras with respect to which a respectiveplurality of video recordings of the video cameras are available forviewing. The video recordings have portions within which there is anabove-threshold likelihood of appearance of an individual or objecthaving been identified as being of interest. The method also includesplotting, based on the plurality of camera identifications and times onthe x-axis associated with the portions of the video recordings, n imagethumbnails on the two dimensional graph, where n is an integer greaterthan two. The n image thumbnails are visually representative of theportions of the video recordings. A first of the n thumbnails is shownearliest in time along the x-axis and the nth thumbnail is shown latestin time along the x-axis. The method also includes allowing selection ofat least one of the n image thumbnails to be removed from the twodimensional graph. The method also includes removing the at least one ofthe n image thumbnails from the two dimensional graph. The method alsoincludes recording that the individual or object is absent in theportion of the video recording associated with the removed thumbnail.

According to another example embodiment, there is provided a tangible,non-transitory, computer-readable storage medium having instructionsencoded therein, wherein the instructions, when executed by at least oneprocessor, cause a carrying out of a method that includes displaying atwo dimensional graph having date and time along the x-axis and, alongthe y-axis, a listing of a plurality of camera identifications of videocameras with respect to which a respective plurality of video recordingsof the video cameras are available for viewing. The video recordingshave portions within which there is an above-threshold likelihood ofappearance of an individual or object having been identified as being ofinterest. The method to be carried out by the instructions encoded inthe storage medium also includes plotting, based on the plurality ofcamera identifications and times on the x-axis associated with theportions of the video recordings, n image thumbnails on the twodimensional graph, where n is an integer greater than two. The n imagethumbnails are visually representative of the portions of the videorecordings, and a first of the n thumbnails is shown earliest in timealong the x-axis and the nth thumbnail is shown latest in time along thex-axis. The method to be carried out by the instructions encoded in thestorage medium also includes allowing selection of at least one of the nimage thumbnails to be removed from the two dimensional graph. Themethod to be carried out by the instructions encoded in the storagemedium also includes removing the at least one of the n image thumbnailsfrom the two dimensional graph. The method to be carried out by theinstructions encoded in the storage medium also includes recording thatthe individual or object is absent in the portion of the video recordingassociated with the removed thumbnail.

BRIEF DESCRIPTION OF THE DRAWINGS

Reference will now be made, by way of example, to the accompanyingdrawings:

FIG. 1 shows a block diagram of an example surveillance system withinwhich methods in accordance with example embodiments can be carried out;

FIG. 2 shows a block diagram of a client-side video review application,in accordance with first example embodiments, that can be providedwithin the example surveillance system shown in FIG. 1;

FIG. 3 illustrates an example user interface page, for the client-sidevideo review application of FIG. 2, plotting thumbnails representativeof portions of video recordings, the user interface page beingconfigured for interaction therewith for identification of sameindividuals or objects in video recordings;

FIG. 4 illustrates, in more detail, one of the thumbnails shown in FIG.3;

FIG. 5 illustrates, in more detail, another one of the thumbnails shownin FIG. 3;

FIG. 6 illustrates another example user interface page, for theclient-side video review application of FIG. 2, plotting thumbnailsrepresentative of portions of video recordings, the illustratedthumbnails being smaller in size than the thumbnails of FIG. 3;

FIG. 7, in more detail, one of the thumbnails shown in FIG. 6;

FIG. 8 is a flow chart illustrating a first user interface-driven methodin accordance with some example embodiments;

FIG. 9 illustrates another example user interface page, for theclient-side video review application of FIG. 2, plotting thumbnailsorganized by the video cameras that took the portions of the videorecordings corresponding to the illustrated thumbnails;

FIG. 10 illustrates an example user interface window for refining asearch in accordance with example embodiments;

FIG. 11 illustrates another example user interface page, for theclient-side video review application of FIG. 2, plotting thumbnails inorder of chronological age with respect to the portions of the videorecordings corresponding to the illustrated thumbnails;

FIG. 12 illustrates an example user interface page similar to the userinterface page of FIG. 11, but containing therein an example videoplayer;

FIG. 13 shows a block diagram of a client-side video review application,in accordance with second alternative example embodiments, that can beprovided within the example surveillance system shown in FIG. 1;

FIG. 14 illustrates an example user interface page, for the client-sidevideo review application of FIG. 13, plotting thumbnails representativeof portions of video recordings;

FIG. 15 illustrates the example user interface page of FIG. 14 in astate where more thumbnails have been reviewed and selected as being amatch to a person or object of interest;

FIG. 16 illustrates one of the thumbnails shown in FIG. 15 in moredetail;

FIG. 17 illustrates another example user interface page, for theclient-side video review application of FIG. 13, this user interfacepage being divided into three main functional regions;

FIG. 18A illustrates an example video player which can be included inuser interface pages such as those illustrated in any one of FIGS. 12,17 and 20 to 22;

FIG. 18B illustrates another example video player which can be includedin user interface pages such as those illustrated in any one of FIGS.12, 17 and 20 to 22;

FIG. 19 is a flow chart illustrating a second user interface-drivenmethod in accordance with some example embodiments;

FIG. 20 illustrates another example user interface page, for theclient-side review application of FIG. 13, this user interface pageagain being divided into three main functional regions;

FIG. 21 illustrates yet another example user interface page, for theclient-side review application of FIG. 13, this user interface pageagain being divided into three main functional regions; and

FIG. 22 illustrates another example user interface page, for theclient-side review application of FIG. 13, this user interface pageassociated with an export function of the client-side reviewapplication.

Similar or the same reference numerals may have been used in differentfigures to denote similar example features illustrated in the drawings.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

It will be understood that when an element is herein referred to asbeing “connected”, “in communication with” or “coupled” to anotherelement, it can be directly connected, directly in communication with ordirectly coupled to the other element or intervening elements may bepresent. In contrast, when an element is herein referred to as being“directly connected”, “directly in communication with” or “directlycoupled” to another element, there are no intervening elements present.Other words used to describe the relationship between elements should beinterpreted in a like fashion (i.e., “between” versus “directlybetween”, “adjacent” versus “directly adjacent”, etc.).

As will be appreciated by one skilled in the art, the various exampleembodiments described herein may be embodied as a method, system, orcomputer program product. Accordingly, the various example embodimentsmay take the form of, for example, an entirely software embodiment(including firmware, resident software, micro-code, etc.) or, as anotherexample, an embodiment combining software and hardware aspects that mayall generally be referred to herein as a “module” or “system.”Furthermore, the various example embodiments may take the form of acomputer program product on a computer-usable storage medium havingcomputer-usable program code embodied in the medium.

Any suitable computer-usable or computer readable medium may beutilized. The computer-usable or computer-readable medium may be, forexample but not limited to, an electronic, magnetic, optical,electromagnetic, infrared, or semiconductor system, apparatus, device,or propagation medium. In the context of this document, acomputer-usable or computer-readable medium may be any medium that cancontain, store, communicate, propagate, or transport the program for useby or in connection with the instruction execution system, apparatus, ordevice.

Computer program code for carrying out operations of various exampleembodiments may be written in an object oriented programming languagesuch as Java, Smalltalk, C++ or the like. However, the computer programcode for carrying out operations of various example embodiments may alsobe written in conventional procedural programming languages, such as the“C” programming language or similar programming languages. The actualprogramming language selected is a matter of design choice and, as willbe appreciated by those skilled in the art, any suitable programminglanguage can be utilized.

Various example embodiments are described below with reference toflowchart illustration(s) and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. Those skilled in the art will understand that various blocksof the flowchart illustration(s) and/or block diagrams, and combinationsof blocks in the flowchart illustration(s) and/or block diagrams, can beimplemented by computer program instructions. These computer programinstructions may be provided to a processor of a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructions,which executed via the processor of the computer or other programmabledata processing apparatus, create means for implementing thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

These computer program instructions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

Reference is now made to FIG. 1 which shows a block diagram of anexample surveillance system 100 within which methods in accordance withexample embodiments can be carried out. Included within the illustratedsurveillance system 100 are one or more computer terminals 104 and aserver system 108. In some example embodiments, the computer terminal104 is a personal computer system; however in other example embodimentsthe computer terminal 104 is a selected one or more of the following: ahandheld device such as, for example, a tablet, a phablet, a smart phoneor a personal digital assistant (PDA); a laptop computer; a smarttelevision; and other suitable devices. With respect to the serversystem 108, this could comprise a single physical machine or multiplephysical machines. It will be understood that the server system 108 neednot be contained within a single chassis, nor necessarily will there bea single location for the server system 108. As will be appreciated bythose skilled in the art, at least some of the functionality of theserver system 108 can be implemented within the computer terminal 104rather than within the server system 108.

The computer terminal 104 communicates with the server system 108through one or more networks. These networks can include the Internet,or one or more other public/private networks coupled together by networkswitches or other communication elements. The network(s) could be of theform of, for example, client-server networks, peer-to-peer networks,etc. Data connections between the computer terminal 104 and the serversystem 108 can be any number of known arrangements for accessing a datacommunications network, such as, for example, dial-up Serial LineInterface Protocol/Point-to-Point Protocol (SLIP/PPP), IntegratedServices Digital Network (ISDN), dedicated lease line service, broadband(e.g. cable) access, Digital Subscriber Line (DSL), AsynchronousTransfer Mode (ATM), Frame Relay, or other known access techniques (forexample, radio frequency (RF) links). In at least one exampleembodiment, the computer terminal 104 and the server system 108 arewithin the same Local Area Network (LAN).

The computer terminal 104 includes at least one processor 112 thatcontrols the overall operation of the computer terminal. The processor112 interacts with various subsystems such as, for example, inputdevices 114 (such as a selected one or more of a keyboard, mouse, touchpad, roller ball and voice control means, for example), random accessmemory (RAM) 116, non-volatile storage 120, display controller subsystem124 and other subsystems [not shown]. The display controller subsystem124 interacts with display 126 and it renders graphics and/or text uponthe display 126.

Still with reference to the computer terminal 104 of the surveillancesystem 100, operating system 140 and various software applications usedby the processor 112 are stored in the non-volatile storage 120. Thenon-volatile storage 120 is, for example, one or more hard disks, solidstate drives, or some other suitable form of computer readable mediumthat retains recorded information after the computer terminal 104 isturned off. Regarding the operating system 140, this includes softwarethat manages computer hardware and software resources of the computerterminal 104 and provides common services for computer programs. Also,those skilled in the art will appreciate that the operating system 140,client-side video review application 144, and other applications 152, orparts thereof, may be temporarily loaded into a volatile store such asthe RAM 116. The processor 112, in addition to its operating systemfunctions, can enable execution of the various software applications onthe computer terminal 104.

More details of the video review application 144 are shown in the blockdiagram of FIG. 2. The video review application 144 can be run on thecomputer terminal 104 and includes a search User Interface (UI) module202 for cooperation with a search session manager module 204 in order toenable a computer terminal user to carry out actions related toproviding input and, more specifically, input to facilitate identifyingsame individuals or objects appearing in a plurality of different videorecordings. In such circumstances, the user of the computer terminal 104is provided with a user interface generated on the display 126 throughwhich the user inputs and receives information in relation the videorecordings.

The video review application 144 also includes the search sessionmanager module 204 mentioned above. The search session manager module204 provides a communications interface between the search UI module 202and a query manager module 164 (FIG. 1) of the server system 108. In atleast some examples, the search session manager module 204 communicateswith the query manager module 164 through the use of Remote ProcedureCalls (RPCs).

Besides the query manager module 164, the server system 108 includesseveral software components for carrying out other functions of theserver system 108. For example, the server system 108 includes a mediaserver module 168. The media server module 168 handles client requestsrelated to storage and retrieval of video taken by video cameras 169 inthe surveillance system 100. The server system 108 also includes ananalytics engine module 172. The analytics engine module 172 can, insome examples, be any suitable one of known commercially availablesoftware that carry out mathematical calculations (and other operations)to attempt computerized matching of same individuals or objects asbetween different portions of video recordings (or as between anyreference image and video compared to the reference image). For example,the analytics engine module 172 can, in one specific example, be asoftware component of the Avigilon Control Center™ server software soldby Avigilon Corporation. In another example, the analytics engine module172 can be a software component of the Qognify Suspect Search™ productsold by Qognify UK Ltd. In some examples the analytics engine module 172can uses the descriptive characteristics of the person's or object'sappearance. Examples of these characteristics include the person's orobject's shape, size, textures and color.

The server system 108 also includes a number of other softwarecomponents 176. These other software components will vary depending onthe requirements of the server system 108 within the overall system. Asjust one example, the other software components 176 might includespecial test and debugging software, or software to facilitate versionupdating of modules within the server system 108. The server system 108also includes one or more data stores 190. In some examples, the datastore 190 comprises one or more databases 191 which facilitate theorganized storing of recorded video.

Regarding the video cameras 169, each of these includes a camera module198. In some examples, the camera module 198 includes one or morespecialized chips to facilitate processing and encoding of video beforeit is even received by the server system 108. For instance, thespecialized chip may be a System-on-Chip (SoC) solution including bothan encoder and a Central Processing Unit (CPU). These permit the cameramodule 198 to carry out the processing and encoding functions. Also, insome examples, part of the processing functions of the camera module 198includes creating metadata for recorded video. For instance, metadatamay be generated relating to one or more foreground areas that thecamera module 198 has detected, and the metadata may define the locationand reference coordinates of the foreground visual object within theimage frame. For example, the location metadata may be further used togenerate a bounding box, typically rectangular in shape, outlining thedetected foreground visual object. The image within the bounding box maybe extracted for inclusion in metadata. The extracted image mayalternately be smaller then what was in the bounding box or may belarger then what was in the bounding box. The size of the image beingextracted can also be close to, but outside of, the actual boundaries ofa detected object.

In some examples, the camera module 198 includes a number of submodulesfor video analytics such as, for instance, an object detectionsubmodule, an instantaneous object classification submodule, a temporalobject classification submodule and an object tracking submodule.Regarding the object detection submodule, such a submodule can beprovided for detecting objects appearing in the field of view of thecamera 169. The object detection submodule may employ any of variousobject detection methods understood by those skilled in the art such as,for example, motion detection and/or blob detection.

Regarding the object tracking submodule that may form part of the cameramodule 198, this may be operatively coupled to both the object detectionsubmodule and the temporal object classification submodule. The objecttracking submodule would be included for the purpose of temporallyassociating instances of an object detected by the object detectionsubmodule. The object tracking submodule may also generate metadatacorresponding to visual objects it tracks.

Regarding the instantaneous object classification submodule that mayform part of the camera module 198, this may be operatively coupled tothe object detection submodule and employed to determine a visualobjects type (such as, for example, human, vehicle or animal) based upona single instance of the object. The input to the instantaneous objectclassification submodule may optionally be a sub-region of an image inwhich the visual object of interest is located rather than the entireimage frame.

Regarding the temporal object classification submodule that may formpart of the camera module 198, this may be operatively coupled to theinstantaneous object classification submodule and employed to maintainclass information of an object over a period of time. The temporalobject classification submodule may average the instantaneous classinformation of an object provided by the instantaneous classificationsubmodule over a period of time during the lifetime of the object. Inother words, the temporal object classification submodule may determinea type of an object based on its appearance in multiple frames. Forexample, gait analysis of the way a person walks can be useful toclassify a person, or analysis of the legs of a person can be useful toclassify a bicycler. The temporal object classification submodule maycombine information regarding the trajectory of an object (e.g. whetherthe trajectory is smooth or chaotic, whether the object is moving ormotionless) and confidence of the classifications made by theinstantaneous object classification submodule averaged over multipleframes. For example, determined classification confidence values may beadjusted based on the smoothness of trajectory of the object. Thetemporal object classification submodule may assign an object to anunknown class until the visual object is classified by the instantaneousobject classification submodule subsequent to a sufficient number oftimes and a predetermined number of statistics having been gathered. Inclassifying an object, the temporal object classification submodule mayalso take into account how long the object has been in the field ofview. The temporal object classification submodule may make a finaldetermination about the class of an object based on the informationdescribed above. The temporal object classification submodule may alsouse a hysteresis approach for changing the class of an object. Morespecifically, a threshold may be set for transitioning theclassification of an object from unknown to a definite class, and thatthreshold may be larger than a threshold for the opposite transition(for example, from a human to unknown). The temporal objectclassification submodule may aggregate the classifications made by theinstantaneous object classification submodule.

In some examples, the camera module 198 is able to detect humans andextract images of humans with respective bounding boxes outlining thehuman objects for inclusion in metadata which along with the associatedvideo may transmitted to the server system 108. At the system 108, themedia server module 168 can process extracted images and generatesignatures (e.g. feature vectors) to represent objects. In computervision, a feature descriptor is generally known as an algorithm thattakes an image and outputs feature descriptions or feature vectors.Feature descriptors encode information, i.e. an image, into a series ofnumbers to act as a numerical “fingerprint” that can be used todifferentiate one feature from another. Ideally this information isinvariant under image transformation so that the features may be foundagain in another image of the same object. Examples of featuredescriptor algorithms are SIFT (Scale-invariant feature transform), HOG(histogram of oriented gradients), and SURF (Speeded Up RobustFeatures).

In accordance with at least some examples, a feature vector is ann-dimensional vector of numerical features (numbers) that represent animage of an object processable by computers. By comparing the featurevector of a first image of one object with the feature vector of asecond image, a computer implementable process may determine whether thefirst image and the second image are images of the same object.

Similarity calculation can be just an extension of the above.Specifically, by calculating the Euclidean distance between two featurevectors of two images captured by one or more of the cameras 169, acomputer implementable process can determine a similarity score toindicate how similar the two images may be.

In accordance with at least some examples, storage of feature vectorswithin the surveillance system 100 is contemplated. For instance,feature vectors may are indexed and stored in the database 191 withrespective video. The feature vectors may also be associated withreference coordinates to where extracted images of respective objectsare located in respective video. Storing may include storing video with,for example, time stamps, camera identifications, metadata with thefeature vectors and reference coordinates, etc.

Reference will now be made to FIG. 3 which is a screen shot of anexample user interface page that can be interacted with for identifyingsame individuals or objects in video recordings in accordance with someexample embodiments. In at least one example, the video reviewapplication 144 (FIG. 1) generates user interface page 510 on thedisplay 126 through which requests will be inputted for processing bythe query manager module 164 on the server system 108.

Within the user interface page 510 is a two dimensional graph 520. Thetwo dimensional graph 520 includes date and time along x-axis 526. Inthe illustrated example, each five minute interval is labelled startingat 9:25 AM at the far left of the x-axis 526 and ending at 10:50 AM atthe far right of the x-axis 526. The interval of time between the twoends of the x-axis 526 can be increased or decreased by use of theslider tool 538. In particular, a moveable knob 544 can be moved betweena left end and a right end of the slider tool 538. The left end of theslider tool 538 corresponds to setting the interval of time between thetwo ends of the x-axis 526 to a maximum (as indicated by the “minus”magnifying glass symbol 546). The right end of the slider tool 538corresponds to setting the interval of time between the two ends of thex-axis 526 to a minimum (as indicated by the “plus” magnifying glasssymbol 550).

The two dimensional graph 520 also includes, along a y-axis 530 of thegraph 520, a listing of a plurality of camera identifications 534 ofvideo cameras with respect to which a respective plurality of videorecordings of the video cameras are available for viewing. Each one ofthe plurality of camera identifications 534 corresponds to a respectiveone of the plurality of video cameras 169 (FIG. 1) that is located in aunique known physical location with respect to all locations of theplurality of video cameras 169 of the surveillance system 100.

On the two dimensional graph 520 are plotted n image thumbnails, where nis an integer greater than two. The n image thumbnails are visuallyrepresentative of certain portions of the video recordings (explained inmore detail subsequently). A first of the n thumbnails, thumbnail 554,is shown earliest in time along the x-axis which, in this example, is atapproximately 9:25 AM on Friday, Feb. 12, 2016. A last (or n^(th))thumbnail, thumbnail 558, is shown latest in time along the x-axiswhich, in this example, is at approximately 10:50 AM on Friday, Feb. 12,2016.

Between the thumbnail 554 and the thumbnail 558 are various interveningthumbnails (fifteen intervening thumbnails in this example; however, inother examples, the number of intervening thumbnails can be, forinstance, significantly larger than fifteen or, in yet other examples,significantly fewer than fifteen such as, for instance, as few as one ornone). Also, it is noted that thumbnail 559 has a check mark in it and abox around it. This is to indicate that the thumbnail 559 is thereference image. The reference image is the image with respect to whichall other relevant images are compared against to determine a likelihoodof a match.

Lines 560 each connect one of the thumbnails with another thumbnail thatis proximate to the other thumbnail in time (usually the most proximateone). Some of the lines 560 are fully solid. For example, the linebetween the thumbnail 559 and thumbnail 566 is fully solid. Others ofthe lines 560 are at least partly dotted. For example, the line betweenthe thumbnail 570 and thumbnail 574 is partly dotted. In the illustratedexample, the fully solid line means that the thumbnails connected atboth ends of the line are both associated with respective portions ofvideo recordings that are above a first threshold for likelihood ofappearance of an individual or object having been identified as being ofinterest. By contrast, the partly dotted line means that the thumbnailconnected at the later-in-time end of the line is associated with arespective portion of a video recording that is below the firstthreshold for likelihood of appearance of an individual or object havingbeen identified as being of interest, but still above a second lowerthreshold as set by slider tool 578.

As mentioned above, the slider tool 578 allows a person interacting withthe user interface page 510 to set a filtering threshold as to which ofthe thumbnails are permitted to appear on the graph 520. In thisexample, a high level of filtering means that only those thumbnailscorresponding to a portion of a video recording where there is a fairlyhigh likelihood of appearance of the individual or object of interestare permitted to appear on the graph 520. By contrast, a low level offiltering means that it will be expected that more thumbnails willappear on the graph 520, including even those thumbnails correspondingto a portion of a video recording where there is a fairly low likelihoodof appearance of the individual or object of interest. Moveable knob 580can be moved between an upper end and a lower end of the slider tool578. The lower end of the slider tool 578 corresponds to setting thefiltering threshold to a minimum (as indicated by the word “Low” onsymbol 582). The upper end of the slider tool 578 corresponds to settingthe filtering threshold to a maximum (as indicated by the word “High” onsymbol 584). Also, it is noted that, in the illustrated example, eachthumbnail includes a visual indication of the likelihood of appearanceof the individual or object of interest. Specifically, there is anindication bar at the bottom of each thumbnail. With reference to FIG.4, indication bar 590 extends from a left side 592 of the thumbnail 570towards a right side 593 of the thumbnail. The wide indication bar 590indicates that the thumbnail 570 corresponds to a portion of a videorecording where there is a higher likelihood of appearance of theindividual or object of interest as compared to a portion of anothervideo recording given a thumbnail having a comparatively narrowindication bar. For example, as shown in FIG. 5, the thumbnail 574 has anarrower indication bar 595 than the indication bar 590 of the thumbnail570.

Reference will now be made to FIG. 6. As mentioned before, the intervalof time between the two ends of the x-axis 526 can be increased ordecreased by use of the slider tool 538. FIG. 6 illustrates the impacton the graph 520 when, relative to what is shown in FIG. 3, the moveableknob 544 is moved closer to the “minus” magnifying glass 546 (i.e. theinterval of time between the two ends of the x-axis 526 is increased).As one example of the impact, thumbnails 602 shown in FIG. 6 are quitesmaller in size as compared to the thumbnails in FIG. 3 (e.g. thethumbnails 559, 566, etc.). This is to be expected because, for example,there are many more thumbnails to plot in this version of the graph ascompared to the previous version of the graph illustrated in FIG. 3(i.e. seventy four thumbnails versus seventeen thumbnails). Because ofthe reduction in size, there is no longer a representative imageprovided on the thumbnail. Instead these smaller thumbnails include onlybar-type indications.

As the bar-type indications of the thumbnails 602 are not the same asthose of the thumbnails 560 shown FIG. 3, the differences are nowpresently explained. Firstly, it will be understood that, a portion of avideo recording to which a thumbnail corresponds is not necessarily of aminute or tiny duration and could be, for example, several minutes long.Thus, it is possible that a portion of a video recording to which athumbnail corresponds can be further sub-divided into yet furtherportions, and likelihood of appearance of the individual or object ofinterest may vary as between each of these further portions. Forexample, say that a complete portion of a video recording is fourminutes long. It could be that a first minute of the four minutes ofvideo recording has an associated first likelihood of appearance of theindividual or object of interest. Next a second minute of the fourminutes of video recording has an associated second likelihood ofappearance of the individual or object of interest which is greater thanthe first likelihood of appearance. Finally, a last two minutes of thefour minutes of the video recording has an associated third likelihoodof appearance of the individual or object of interest which is greaterthan the second likelihood of appearance.

In order to present these differences in likelihoods of appearance to aperson interacting with the user interface page 510, the thumbnailsthemselves can provide a miniature graphical representation oflikelihood of appearance as a function of time. With reference now toFIGS. 6 and 7, thumbnail 702 is one such thumbnail. During a first timeperiod x₁, the first likelihood of appearance is represented by a firstheight h of bar graph 710. During a second time period x₂, the secondlikelihood of appearance is represented by a second height i of bargraph 710. It will be noted that the height i is greater than the heighth, indicating that likelihood of appearance is greater during the secondtime period than during the first time period. During a third timeperiod x₃, the third likelihood of appearance is represented by a thirdheight j of bar graph 710. It will be noted that the height j is greaterthan the height i, indicating that likelihood of appearance is greaterduring the third time period than during the second time period.

Reference will now be made to FIG. 8 which is a flow chart illustratinga method 750 in accordance with example embodiments. As a first action(752) in the illustrated method 750, a two dimensional graph isdisplayed, where the two dimensional graph has date and time along thex-axis and, along the y-axis, a listing of a plurality of camera IDs ofvideo camera. The two dimensional graph can be displayed within, forexample, a user interface page such as, for instance, the user interfacepage 510 illustrated in FIGS. 3 and 6.

Next the method 750 includes plotting (754) n image thumbnails on thetwo dimensional graph, where the plotting is based on the plurality ofcamera IDs and times on the x-axis associated with the portions of thevideo recordings. Regarding the above action 754, more detailsconcerning this have been shown and described in FIGS. 3 and 6 and theassociated description for those figures.

Next the method 750 includes allowing selection (756) of at least one ofthe n image thumbnails to be removed from the two dimensional graph. Forexample, take for instance the thumbnail 574 shown in FIGS. 3 and 5. Auser of the computer terminal 104 may determine that the person shown inthe portion of the video recording associated with the thumbnail 574 isnot the individual of interest. Accordingly, the user may select thethumbnail 574 for removal from the two dimensional graph. The specificuser interface actions for carrying this out may take any one of avariety of different forms understood by those skilled in the art. Forexample, by moving a cursor over the thumbnail 574 an “x” symbol couldappear (or alternatively the “x” could be permanently visible) and theuser could then click on the “x” to provide input into the client-sidevideo review application (the input being that the thumbnail 574 isselected for removal from the two dimensional graph). As an alternativeexample, the user could be permitted to click on one or more thumbnails,these one or more thumbnails would then become highlighted, and then afinal icon (for instance, a trash can icon within the user interfacepage 510) could be selected to make the one or more thumbnailscollectively removed.

Next the method 750 includes removing (758) the at least one of the nimage thumbnails from the two dimensional graph. For example, thethumbnail 574 could be removed from the two dimensional graph shown inFIG. 3 subsequent to the action 756.

Finally the method 750 includes recording (760) that the individual orobject is absent in the portion of the video recording corresponding tothe removed thumbnail. The recording may be in the RAM 116 (FIG. 1)and/or the non-volatile storage 120 of the computer terminal 104.Contemporaneously (or at a later point in time) the database 191 of thestorage 190 may record this change as well.

Reference with now be made to FIG. 9 which illustrates a screen shot ofanother example user interface page 810 that can be interacted with foridentifying same individuals or objects in video recordings inaccordance with some example embodiments. In at least one example, thevideo review application 144 (FIG. 1) generates the user interface page810 on the display 126 through which requests will be inputted forprocessing by the query manager module 164 on the server system 108.

In the example user interface page 810, thumbnails 820 are organizedaccording to which of the video cameras 169 (FIG. 1) that are identifiedas having taken the portions of the video recordings corresponding tothe illustrated thumbnails 820. Thus, it will be seen that there areseven thumbnails available under camera “Left Multisensor (1)(LID 91)”.There are six thumbnails available under camera “Center Multisensor(2)(LID 92)”. There are two thumbnails available under camera “RightMultisensor (3)(LID 93)”. Finally, there are two thumbnails availableunder camera “16L-H4PRO-B (LID 20)”. Organization by some parameterother than specific video camera is possible. More specifically, theillustrated user interface page 810 includes a drop-down selector 822which permits thumbnail organization by a different parameter (forexample, by chronological age, as will be later herein described inrelation to FIG. 11).

The thumbnails 820 in FIG. 9 are somewhat similar to those of FIG. 3;however, because they are larger in size, written information can beincluded at the bottom of them including percentage likelihood ofappearance, name of the corresponding video camera and time stamp. Inaccordance with at least one example embodiment, single clicking on anyof the thumbnails 820 will bring the user to a starting point in theportion of the video corresponding to that thumbnail. By contract,double clicking on any of the thumbnails 820 will bring the user to theexact point in the video as shown in the thumbnail image.

Slider tool 828 functions in a manner similar to the slider tool 578previously discussed in connection with FIG. 3, and thus the slider tool828 allows a person interacting with the user interface page 810 to seta filtering threshold as to which of the thumbnails 820 are permitted toappear on the user interface page 810. As in the previous example, ahigh level of filtering means that only those thumbnails correspondingto a portion of a video recording where there is a fairly highlikelihood of appearance of the individual or object of interest arepermitted to appear on the user interface page 810. By contrast, a lowlevel of filtering means that it will be expected that there will bemore thumbnails appearing on the user interface page 810, including eventhose thumbnails corresponding to a portion of a video recording wherethere is a fairly low likelihood of appearance of the individual orobject of interest. Moveable knob 880 can be moved between an upper endand a lower end of the slider tool 828. The lower end of the slider tool828 corresponds to setting the filtering threshold to a minimum (asindicated by the word “Low” on symbol 882). The upper end of the slidertool 828 corresponds to setting the filtering threshold to a maximum (asindicated by the word “High” on symbol 884). Also, it is noted that, insome examples, each of the thumbnails 820 can include a visualindication of the likelihood of appearance of the individual or objectof interest. Specifically, there can be an indication bar in the bottomhalf of each thumbnail. This indication bar has already been explainedin connection with FIGS. 4 and 5. Additionally, it is noted that,specifically for these larger thumbnails, a percentage likelihood ofappearance (i.e. some amount between 1% and 100%) can be shown assuperimposed on the indication bar.

In the user interface page 810 shown in FIG. 9, all the video cameras169 are included (four cameras are shown in the screen area; howevermore are available just by scrolling down the user interface page 810using the icon 890). In accordance with some examples, a computerterminal user can have control over which of the video cameras 169 areincluded on the user interface page 810. For example, by clicking“Refine Search” icon 894, the computer terminal user can cause a newinterface window 910 to be provided as shown in FIG. 10.

The illustrated interface window 910 includes three window areas: acamera list area 912, a reference image area 914 and a date and timeadjustor area 916. The camera list in the camera list area 912 isorganized as a hierarchy of check boxes. At the highest level in thehierarchy is a check box 919 which corresponds to all video cameraslocated at “Chicago Site” (hereinafter this hierarchical level will bereferred to as the site level). Putting a check in the check box 919initially causes all of the cameras at the Chicago Site to becomeselected. Similarly unchecking the check box 919 will cause all of thecameras at the Chicago Site to become unselected. At the next level inthe hierarchy are check boxes 920, 922, 924 and 926 which correspond togeographical areas at the Chicago Site (hereinafter this hierarchicallevel will be referred to as the geographical area level). In theillustrated example, the check box 920 corresponds to the geographicalarea of “North Side of Building”, the check box 922 corresponds to thegeographical area of “East Parking Lot”, the check box 924 correspondsto the geographical area of “West Pipe Yard”, and the check box 926corresponds to the geographical area of “Manufacturing”. Putting a checkin the check box corresponding to a geographical area level initiallycauses all of the cameras organized under that specific geographicalarea level to become selected. So, for instance, if the check box 920 ischecked, this will initially cause all of the check boxes 930, 932 and934 associated with cameras “Left Multisensor (1)(LID 91)”, “CenterMultisensor (2)(LID 92)”, and “Right Multisensor (3)(LID 93)”respectively to become checked (hereinafter the hierarchical level ofindividual video cameras will be referred to as the camera level).Similarly, unchecking a check box corresponding to a geographical arealevel will cause all of the cameras organized under that specificgeographical area level to become unselected. So, for instance, if thecheck box 920 is unchecked, this will cause all of the check boxes 930,932 and 934 associated with cameras “Left Multisensor (1)(LID 91)”,“Center Multisensor (2)(LID 92)”, and “Right Multisensor (3)(LID 93)”respectively to become unselected.

Still with reference to FIG. 10, the reference image area 914 is in thetop, right region of the interface window 910. As mentioned before, thereference image is the image with respect to which all other relevantimages are compared against to determine a likelihood of a match. Alsowithin the illustrated interface window 910, below the reference imagearea 914, is the date and time adjustor area 916. The date and timeadjustor area 916 provides the computer terminal user the ability tochange the date and time range of the search. In particular, either leftend 950 or right end 954 of the dark colored bar can be moved relativeto the entire length of time/date line 956. Moving either the left end950 to the left or the right end 954 to the right increases the totaltime/date range of the search. Similarly moving either the left end 950to the right or the right end 954 to the left decreases the totaltime/date range of the search. In accordance with at least one exampleembodiment, the right end of the time/date line 956 can be as recent intime as a few minutes before the current time at which the client-sidevideo review application is being run. Those skilled in the art willappreciate that adjusting a time/date line to include very recent videorecordings is not limited to the example interface window 910, but isindeed can be applicable to other example embodiments herein describedas well.

Once all desired changes have been made within the interface window 910,the search can be updated to reflect the parameters that have beenchanged by the computer terminal user. In the illustrated example thecomputer terminal user can initiate this by clicking on “SEARCH” icon970. The video review application 144 then returns the computer terminaluser to an updated version of the user interface page 810.

On another note regarding the interface window 910 illustrated in FIG.10, it will be understood that its application is not limited to theexample embodiment of FIG. 9. The interface window 910 is also suitablefor other example embodiments such as, for instance, the exampleembodiment of FIG. 20 that will be later herein described.

Reference will now be made to FIG. 11 which illustrates a screen shot ofanother example user interface page 1010 that can be interacted with foridentifying same individuals or objects in video recordings inaccordance with some example embodiments. In at least one example, thevideo review application 144 (FIG. 1) generates the user interface page1010 on the display 126 through which requests will be inputted forprocessing by the query manager module 164 on the server system 108.

The user interface page 1010 is similar to the user interface page 810shown in FIG. 9; however organization of thumbnails is by chronologicalage rather than by specific video cameras. Thus, it will be seen thatupper and left most thumbnail 1030 corresponds to a portion of a videorecording earliest in time, beginning at around 9:25 AM. Next in time isa portion of a video recording beginning at around 9:41 AM (thumbnail1032). After that is a portion of a video recording beginning at around10:13 AM (thumbnail 1034). Thus, the organization followed is orderingthumbnails from left to right for each row, starting with an uppermostrow, then proceeding down to next rows following the same left to rightordering or, by way of analogy, the organization is similar to how wordswould be ordered on pages of any sort of English language book orpublication. The thumbnails in FIG. 11 follow the same formatting, styleand content as the thumbnails 820 of FIG. 9. For example, like thethumbnails in FIG. 9 the thumbnails in FIG. 11 can have writteninformation included at the bottom of them including, for example,percentage likelihood of appearance, name of the corresponding videocamera and time stamp. In the illustrated example, many thumbnails areshown in the screen area; however even more thumbnails are availablejust by scrolling down the user interface page 1010 using the icon 1090.

Slider tool 1078 functions in a manner similar to the slider tool 578previously discussed in connection with FIG. 3, and thus the slider tool1078 allows a person interacting with the user interface page 1010 toset a filtering threshold as to which of the illustrated thumbnails arepermitted to appear on the user interface page 1010. As in the previousexample, a high level of filtering means that only those thumbnailscorresponding to a portion of a video recording where there is a fairlyhigh likelihood of appearance of the individual or object of interestare permitted to appear on the user interface page 1010. By contrast, alow level of filtering means that it will be expected that there will bemore thumbnails appearing on the user interface page 1010, includingeven those thumbnails corresponding to a portion of a video recordingwhere there is a fairly low likelihood of appearance of the individualor object of interest. Moveable knob 1080 can be moved between an upperend and a lower end of the slider tool 1078. The lower end of the slidertool 1078 corresponds to setting the filtering threshold to a minimum(as indicated by the word “Low” on symbol 1082). The upper end of theslider tool 1078 corresponds to setting the filtering threshold to amaximum (as indicated by the word “High” on symbol 1084). Also, it isnoted that, in some examples, each of the thumbnails can include avisual indication of the likelihood of appearance of the individual orobject of interest. Specifically, there can be an indication bar in thebottom half of each thumbnail. This indication bar has already beenexplained in connection with FIGS. 4 and 5. Additionally, it is notedthat, specifically for these larger thumbnails, a percentage likelihoodof appearance (i.e. some amount between 1% and 100%) can be shown assuperimposed on the indication bar.

In some examples, the thumbnails can be clicked on by the computerterminal user to bring up a video player allowing the computer terminaluser to watch the portion of the video recording corresponding to theselected thumbnail. For instance, with reference to FIGS. 11 and 12, thethumbnail 1030 can be clicked on by the computer terminal user (forexample, as previously described, single clicking on the thumbnail 1030may bring the user to a starting point in the portion of the videocorresponding to that thumbnail, and double clicking on the thumbnail1030 may bring the user to the exact point in the video as shown in thethumbnail image). The clicking action changes the user interface page1010 into a new user interface page 1110 that is similar to the userinterface page 1010 but includes video player 1120. The video player1120 plays the portion of the video recording corresponding to thethumbnail 1030. In this manner the computer terminal user can watch theportion of the video recording and hopefully by watching this thecomputer terminal user can see or notice something that will allow adecision to be made as to whether or not the individual or object ofinterest actually appears in the portion of the video recordingcorresponding to the thumbnail 1030. It will be appreciated that theabove-described user interface page transformation in respect of which avideo player appears upon clicking of a thumbnail is not just limited tothe example embodiments of FIGS. 11 and 12. It is equally applicable toother relevant example embodiments including, for example, those shownin FIGS. 3, 6 and 9.

Reference will now be made to FIG. 13 which shows a block diagram of aclient-side video review application 144′ for the example surveillancesystem shown in FIG. 1. There are similarities between the video reviewapplication 144′ and the video review application 144 describedpreviously. For example, both video review applications relate toproviding a UI to collect input for facilitating the identification ofsame individuals or objects appearing in a plurality of different videorecordings. Further similarities will become apparent from thedescription which follows.

The video review application 144′ can be run on the computer terminal104 (FIG. 1) and includes a search UI module 1302 for cooperation with asearch session manager module 1304 in order to enable a computerterminal user to carry out actions related to providing input and, morespecifically, input to facilitate identifying same individuals orobjects appearing in a plurality of different video recordings. In suchcircumstances, the user of the computer terminal 104 is provided with auser interface generated on the display 126 through which the userinputs and receives information in relation the video recordings.

The video review application 144′ also includes the search sessionmanager module 1304 mentioned above. The search session manager module1304 provides a communications interface between the search UI module1302 and a query manager module 164 (FIG. 1) of the server system 108.In at least some examples, the search session manager module 1304communicates with the query manager module 164 through the use of RemoteProcedure Calls (RPCs).

Reference will now be made to FIG. 14 which is a screen shot of anexample user interface page 1410 that can be interacted with foridentifying same individuals or objects in video recordings inaccordance with some example embodiments. In at least one example, thevideo review application 144′ (FIG. 13) generates the user interfacepage 1410 on the display 126 (FIG. 1) through which requests will beinputted for processing by the query manager module 164 on the serversystem 108.

Within the user interface page 1410 is a two dimensional graph 1422. Thetwo dimensional graph 1422 includes date and time along x-axis 1426. Inthe illustrated example, each twenty minute interval is labelledstarting at 2:40 PM near the far left of the x-axis 1426 and ending at5:00 PM at the far right of the x-axis 1426. In at least some examples,the interval of time between the two ends of the x-axis 1426 can beincreased or decreased. For instance, the user interface page 1410 mightinclude a slider tool similar to the slider tool 538 described inconnection with the user interface page 510 (FIG. 3). In at least oneexample, the slider tool can change the granularity of the time intervalfrom anywhere between 1 minute to 30 minutes. Of course othergranularity ranges are possible.

The two dimensional graph 1422 also includes, along a y-axis 1430 of thegraph 1422, a listing of a plurality of camera identifications 1434 ofvideo cameras with respect to which a respective plurality of videorecordings of the video cameras are available for viewing. Each one ofthe plurality of camera identifications 1434 corresponds to a respectiveone of the plurality of video cameras 169 (FIG. 1) that is located in aunique known physical location with respect to all locations of theplurality of video cameras 169 of the surveillance system 100. Theorganization of the listing of the plurality of camera identifications1434 may be such that it is in descending order (from top to bottom)based those camera identification having the most markers. Alternativelyother forms of organization of the listing of the plurality of cameraidentifications 1434 are contemplated.

Underneath the two dimensional graph 1422 is a plurality of imagethumbnails 1450 organized into columns. Each column is assigned aninterval of time so, starting from the leftmost column, a first columnis assigned the time interval of 2:30 PM to 2:39.59 PM. Then the nextcolumn is assigned the time interval of 2:40 PM to 2:49.59 PM, and soon. In this manner, one of the thumbnails should only appear in thefirst column if the associated portion of the video recording for thatthumbnail falls within the time interval of 2:30 PM to 2:39.59 PM.Otherwise the thumbnail needs to go in whichever of the columns is thematching time interval. Also, those skilled in the art will appreciatethat the above described organization into columns is not critical. Forexample, organization into rows would be a suitable alternative designchoice.

It will be noted that in each of the thumbnail columns the thumbnails1450 are organized in an order that is based on the likelihood ofappearance of the individual or object having been identified as beingof interest. This can be seen from an indicia provided on each of thethumbnails 1450. In the illustrated example, this indicia takes the formof a circle 1452 within which is displayed a percentage number (thisdetail of the indicia is too small to be illustrated in FIG. 14)corresponding to likelihood of appearance of an individual or objecthaving been identified as being of interest. Taking the leftmost columnas an example, the percentage number corresponding to the top thumbnailis 87%, the next thumbnail below that one is 84%, then the nextthumbnail below that one is 81%, and so on.

Within the illustrated user interface page 1410 there is also athumbnail 1462 positioned above the two dimensional graph 1422 andvertically aligned with a thumbnail column corresponding to the timeinterval of 3:00 PM to 3:09.59 PM. The thumbnail 1462 is different fromthe thumbnails below the graph 1422 in that a user of the computerterminal 104 (FIG. 1) provided, at some preceding moment, input that thegirl in the thumbnail is the particular individual having beenidentified as being of interest (i.e. 100% likelihood of being a match).This was done, at the preceding moment, by moving cursor 1466 across theuser interface page 1410 and clicking on one of the thumbnails below thegraph 1422. Once then thumbnail is clicked on it moves up above thegraph 1422 while still remaining vertically aligned with the thumbnailcolumn it came from.

It will also be noted that the thumbnail 1462 has a corresponding marker1470 on the graph 1422. In this illustrated example, the marker 1470indicates that the girl of interest appears in a portion of a videorecording taken by video camera “cam-1002” during the time interval of3:00 PM to 3:09.59 PM.

Reference will now be made to FIG. 15. FIG. 15 illustrates the impact onelements displayed in the user interface 1410, relative to what is shownin FIG. 14, after more of the thumbnails below the graph 1422 areclicked on. The main interactive changes occurring when more thumbnailsare clicked on are that more markers appear on the graph 1422, morethumbnails are appearing above the graph 1422 and thumbnails below thegraph 1422 become rearranged and changed (including the addition of newthumbnails not previously shown and the removal of thumbnails no longerhaving a sufficient match likelihood). It will be noted that each timeone of the thumbnails is clicked on this adds new information in termsof what is likely to be and what is not likely to be a match. In otherwords, the new information is relevant to searches. In some examples,the system takes the user's feedback to refine the search results (bymerging the result of multiple query images). In such examples the userinterface can allow for collecting the feedback of the user for thepurpose of collecting ground truth data that can be used to refine anengine (or to train a new engine). This feedback mechanism can be usedto create a system that evolves by continuously and automaticallylearning from users.

Thus, an updated search is run whenever one of the thumbnails is clickedon. Also, a selector 1501 is provided to permit selecting a differentengine (neural network) to run the search should this be desired. Aswill be appreciated by those skilled in the art, different searchresults will be produced whenever a different engine is used to run asearch. Thus, in some examples it is possible to allow the computerterminal user to try running a search on different engines until he hasdecided upon an engine that is more suitable than others for hispurpose. Thus, the selector 1501 allows toggling between differentengines, or even to choose multiple engines. With respect to multipleengines, selected algorithms can be used (rank fusion, or featurefusion) that combine the results of multiple engines, in the goal ofyielding results that are in average better than the each of the enginesalone.

Regarding example marker 1502 having an x coordinate on the x-axis 1426at the time interval of 4:10 PM to 4:19.59 PM and having a y coordinateon the y-axis 1430 corresponding to the camera “cam-1008”. This is a newmarker meaning that at some point between illustrated user interfacestates shown in FIGS. 14 and 15, a user of the computer terminal 104(FIG. 1) selected thumbnail 1506 to indicate it as a match for the girlof interest causing it to move up from a vertically aligned column(below the graph 1422) to the shown location above the graph 1422.

It will be noted that for some time intervals there are multiplemarkers. In the illustrated example, the time interval of 3:00 PM to3:09.59 PM includes three markers 1510, 1512 and 1470, the time intervalof 3:50 PM to 3:59.59 PM includes three markers 1516, 1518 and 1520, andthe time interval of 4:20 PM to 4:29.59 PM includes two markers 1520 and1522. Also, as regards to a marker falling within one time interval anda marker falling within a next time interval, a line is created betweenthe two markers. For example, marker 1540 falls with the time intervalof 3:10 PM to 3:19.59 PM, and marker 1542 is in the next later timeinterval of 3:20 PM to 3:29.59 PM, and so there is a line 1544 betweenthe marker 1540 and the marker 1542. Lines between markers on the graph1422 have a similar practical significance to the lines 560 that connectthumbnails in the previously discussed FIG. 3 embodiment. Namely each ofthe lines between the markers connect to other line(s) such that a pathis constructed on the graph 1422 showing how and when the individual orobject of interest moved between the video cameras listed along they-axis 1430.

It will be noted that there can be more than one line between markers ina first time interval and a next later time interval. For example, thereare three lines between a marker 1542 in the time interval of 3:20 PM to3:29.59 PM and the markers 1516, 1518 and 1520 in the time interval of3:50 PM to 3:59.59 PM. A first line 1550 connects the marker 1542 in thetime interval of 3:20 PM to 3:29.59 PM to the marker 1516 in the timeinterval of 3:50 PM to 3:59.59 PM. A second line 1552 connects themarker 1542 in the time interval of 3:20 PM to 3:29.59 PM to the marker1518 in the time interval of 3:50 PM to 3:59.59 PM. A third line 1554connects the marker 1542 in the time interval of 3:20 PM to 3:29.59 PMto the marker 1520 in the time interval of 3:50 PM to 3:59.59 PM.

As previously mentioned, the time interval of 3:50 PM to 3:59.59 PMincludes three markers 1516, 1518 and 1520. Since there are threemarkers in this time interval, this means that three thumbnails wereclicked on in the thumbnail column for that time interval, andfurthermore those three thumbnails have been cause to move above thegraph 1422. Nonetheless, only a single thumbnail 1570 is visible becauseof the space constraint within the user interface 1410. In someexamples, the two hidden thumbnails can be revealed, the manner in whichwill now be described with reference to FIG. 16.

FIG. 16 is a close-up illustration of the user interface 1410 within theregion of the thumbnail 1570. On the left side of FIG. 16, the cursor1466 is beside the thumbnail 1570. The next action is for the user tomove and position the cursor 1466 over the thumbnail 1570 as shown onthe right side of FIG. 16. By doing this, two hidden thumbnails 1572 and1574 of thumbnails set 1578 become revealed. Should the user like tobring one of the thumbnails 1572 and 1574 to the front so as to becomefully revealed, the user can intuitively move the cursor over either thethumbnail 1572 or 1574 and then click on it. Also, it will be understoodthat when the clicked on thumbnail moves to the front, the thumbnailholding the front (revealed) position must move to a back location. Thusmovement of thumbnails within the set 1578 can be analogized toshuffling of cards within a deck.

Reference will now be made to FIG. 17 which is a screen shot of anotherexample user interface page 1702, which can be interacted with foridentifying same individuals or objects in video recordings inaccordance with another example embodiment. The user interface page 1702is divided into three functional regions: a first UI region 1710, asecond UI region 1712 and a third UI region 1714. Within the first UIregion 1710, slider tool 1778 functions in a manner similar to theslider tool 1078 previously discussed in connection with FIG. 11, andthus the slider tool 1778 allows a person interacting with the userinterface page 1702 to set a filtering threshold as to which thumbnailsare permitted to appear on the user interface page 1702. Each of thethumbnails 1716 with the user interface page 1702 are organized intocolumns based on the time interval within which the portion of the videorecording associated with the thumbnail falls. Starting from theleftmost column, this column is assigned the time interval of 7:15 PM to7:16 PM. Then the next column is assigned the time interval of 7:16 PMto 7:17 PM, and so on. Thus the organization of thumbnails in thethumbnail columns within the user interface page 1702 has similarity tothe organization of thumbnails in the thumbnail columns within the userinterface page 1410 previous described in connection with FIGS. 14 and15. It is also noted that there are drop-down selectors 1718 and 1719provided within the first UI region 1710. The drop-down selector 1718impacts how the thumbnails 1716 are organized within each of theirrespective columns. In the illustrated example, the drop-down selector1718 has been set to “Relevance”. This means that thumbnailscorresponding to portions of videos where there is a higher likelihoodof appearance of the individual or object of interest will appear closerto the top of the first UI region 1710 than the ones corresponding tolower likelihood of appearance. The drop-down selector 1719 is labelled“Options” and allows the computer terminal user, once clicked on, topick other search-related option such as, for example, initiate anexport of all starred results or bookmark all the starred results. Aswill be appreciated by those skilled in the art, “export” in the contextof recorded video means to move or copy video recording(s) or parts ofvideo recording(s) from one device to another device (for example, forthe purpose of backing up or otherwise saving what is being moved orcopied). “Bookmark” means to create an electronic marker or index tomake it easier for the computer terminal user to return to specificpart(s) of video recording(s).

It will be noted that each of the thumbnails 1716 includes a squaregraphic 1720 in the upper left corner of the thumbnail and a stargraphic 1724 in the upper right corner of the thumbnail. These graphicsare superimposed over the images on the thumbnails 1716. The stargraphic 1724 can be clicked on to indicate that the object or person ofinterest is contained in the portion of the video recordingcorresponding to that thumbnail. When this occurs (also herein referredto as “starring” a result) the star graphic 1724 may change from alight, translucent shading to a solid bright color (although in theillustrated example color is not shown, the star graphic on the upperleft of the thumbnails 1716 has been clicked on to indicate a matchwhereas the other thumbnails 1716 are not). Alternatively the stargraphic 1724 may change in some other manner when clicked on such as,for example, becoming continuously animated once selected to indicatethe match. Regarding the square graphic 1720 in the upper left corner ofeach of the thumbnails 1716, this can be clicked on to indicate that theobject or person of interest is not contained in the portion of thevideo recording corresponding to that thumbnail. When this occurs, a red“X” may appear within the square graphic 1720 to provide visualindication of what has occurred. Also, those skilled in the art willappreciate that the red “X” is simply one of many possible designchoices that can achieve the same result of providing the desiredindication of a non-match. In some examples, the thumbnails in thecolumns will re-position themselves amongst each other when a userclicks on one or more of the thumbnails to indicate matches and/ornon-matches. In other examples, the thumbnails in the columns willremain in a static position when a user clicks on one or more of thethumbnails to indicate matches and/or non-matches.

A video player 1725 is included in the second UI region 1712 within theuser interface page 1702. In the illustrated example, the video player1725 is playing the portion of the video recording corresponding tothumbnail 1727. In this manner the computer terminal user can watch theportion of the video recording and hopefully by watching this thecomputer terminal user can see or notice something that will allow adecision to be made as to whether or not the individual or object ofinterest actually appears in the portion of the video recordingcorresponding to the thumbnail 1727. In the illustrated example,bounding boxes, such as bounding boxes 1729 and 1731, appear around anumber of moving objects and persons within the displayed video. Thebounding box 1731 has the percentage “50%” shown just above the top ofthe bounding box to indicate to the computer terminal user that theperson within the bounding box 1731 is calculated to have a 50%likelihood of being the person of interest. By contrast, the boundingbox 1729 does not have any percentage shown above it. In some examples,whether a percentage is or is not shown will depend upon whether alikelihood of appearance threshold is exceeded (i.e. the likelihood ofappearance information will only appear if it is sufficiently high).

It will be understood that the video player 1725 does not limit thecomputer terminal user to just watching the portion of the videorecording corresponding to the thumbnail 1727. The computer terminaluser can watch other video including those corresponding to any of thethumbnails 1716 shown in the first UI region 1710. In accordance with atleast one example embodiment, single clicking on any of the thumbnails1716 will bring the user to a starting point in the portion of the videocorresponding to that thumbnail. By contract, double clicking on any ofthe thumbnails 1716 will bring the user to the exact point in the videoas shown in the thumbnail image.

Within the third UI region 1714 is a two dimensional graph 1764. The twodimensional graph 1764 includes date and time along x-axis 1765. In theillustrated example, each thirty second interval is labelled starting at7:15 PM at the far left of the x-axis 1765 and ending at 7:21 PM at thefar right of the x-axis 1765. In at least some examples, the interval oftime between the two ends of the x-axis 1765 can be increased ordecreased. For instance, the illustrated user interface page 1702includes a slider tool 1766 similar to the slider tool 538 described inconnection with the user interface page 510 (FIG. 3).

The two dimensional graph 1764 also includes, along a y-axis 1767 of thegraph 1764, a listing of a plurality of camera identifications 1769 ofvideo cameras with respect to which a respective plurality of videorecordings of the video cameras are available for viewing. Each one ofthe plurality of camera identifications 1769 corresponds to a respectiveone of the plurality of video cameras 169 (FIG. 1) that is located in aunique known physical location with respect to all locations of theplurality of video cameras 169 of the surveillance system 100. Theorganization of the listing of the plurality of camera identifications1769 may be such that it is in descending order (from top to bottom)based those camera identification having the most markers. Alternativelyother forms of organization of the listing of the plurality of cameraidentifications 1769 are contemplated. In at least one alternativeexample, the listing of the plurality of camera identifications 1769 canbe made shorter by only showing those cameras having at least onestarred result.

Still with reference to the third UI region 1714, there is a marker 1771plotted at roughly 7:15.30 PM. In this illustrated example, the marker1771 corresponds to the thumbnail in the top left corner of the first UIregion 1710 which, as mentioned, has been marked as a match for theobject or person of interest. To make the correspondence between themarker 1771 and the corresponding thumbnail more apparent, the markercan be displayed in a same color as the star graphic on the thumbnail.

Reference will now be made to FIG. 18A which illustrates an examplevideo player 1800 in accordance with some example embodiments. The videoplayer 1800 can be similar to the video player 1725 included in theinterface page 1702 (FIG. 17) and in fact could certainly be used withinsuch an interface page. Likewise the video player 1800 can be similar toany one of the video players included in the interface pages illustratedin FIGS. 12, 17 and 20 to 22 and in fact could certainly be used withinany one of those interface pages as well.

Within video being shown on the video player 1800 there is a boundingbox 1810 surrounding a man shown in the video. By right clicking on thebounding box 1810, a selection list 1814 appears with a number of optionfor running a search. Clicking on selection option 1816 (“Find more likethis”) initiates a search of stored video within the storage 190(FIG. 1) for anyone that may be likely to match the person within thebounding box 1810. Clicking on selection option 1818 (“Find more likethis person prior to this”) initiates a similar search; however a morerestricted search in the sense that the search will be limited to videooccurring prior in time to date/time stamp 1823 of the displayed framein the video. Clicking on selection option 1820 (“Find more like thisperson after this”) initiates a search that is the complement of thesearch initiated by choosing the option 1818 (i.e. the search will belimited to video occurring afterwards in time relative to date/timestamp 1823 of the displayed frame in the video).

An example of a person losing his bag in a mall is presently describedto show why the restricted search options (i.e. the options 1818 and1820) might be selected over the option 1816. So if a person loses hisbag in a mall, the following should be true: i) at one point in time theperson was within the mall carrying the bag; and ii) at a later point intime the person was within the mall not carrying the bag. So when theperson goes to the security office of the mall, a security guard canstart looking at videos in a video player. As soon as the security guardfinds the person in a portion of a video recording taken at the mall, hecan look at the relevant video frames and see whether the person iscarrying or is not carrying the bag at that time. If it is the case thatthe person is carrying the bag in those video frames, then the securityguard can select the option 1820 because searching backwards in timewill not be of assistance in trying to find any video of the person atthe moment where the bag was lost. By contrast, if it is the case thatthe person is not carrying the bag in those video frames, then thesecurity guard can select the option 1818 because searching forwards intime will not be of assistance in trying to find any video of the personat the moment where the bag was lost. It should be noted that, toinitiate the above described search, it is not critical that thesecurity guard find the person in some portion of a video recordingtaken at the mall. Instead the security guard could, for example, directthe person to stand in front of a video camera in or nearby to thesecurity office. The security guard would then have recorded videoimages of the person which could then be used to initiate the search.

Reference will now be made to FIG. 18B which illustrates another examplevideo player 1850 in accordance with some example embodiments. The videoplayer 1850 can be similar to the video player 1725 included in theinterface page 1702 (FIG. 17) and in fact could certainly be used withinsuch an interface page. Likewise the video player 1850 can be similar toany one of the video players included in the interface pages illustratedin FIGS. 12, 17 and 20 to 22 and in fact could certainly be used withinany one of those interface pages as well.

Within video being shown on the video player 1850 there is a boundingbox 1860 surrounding a man shown in the video. By right clicking on thebounding box 1860, a selection list 1864 appears with a number of optionfor running a search. Clicking on selection option 1868 (“Find more likethis person prior to this”) initiates a search of stored video withinthe storage 190 (FIG. 1) for anyone that may be likely to match theperson within the bounding box 1860, but limited to video occurringprior in time to date/time stamp 1869 of the displayed frame in thevideo. Clicking on selection option 1870 (“Find more like this personafter this”) initiates a search that is the complement of the searchinitiated by choosing the option 1868 (i.e. the search will be limitedto video occurring afterwards in time relative to date/time stamp 1869of the displayed frame in the video). Clicking on selection option 1874(“Additional Search Options”) allows the computer terminal user to pickother search-related option such as, for example, initiate an export ofall starred results or bookmark all the starred results. These optionshave already been herein discussed.

Reference will now be made to FIG. 19 which is a flow chart thatillustrating a method 1900 in accordance with some example embodiments.As a first action in the illustrated method 1900, the client-side videoreview application 144 (FIG. 2) or the client-side video reviewapplication 144′ (FIG. 13) detects a user input, via a video player(e.g. the video player 1800 or the video player 1850) in the userinterface, including bounding box contents selection corresponding tothe person or object to be searched for. As described in connection withthe example illustrated in FIG. 18A or 18B, the computer terminal usercan right click the bounding box 1810 (or the bounding box 1860) to bepresented with different options for selecting a particular type ofsearch to be run. Of course right clicking to bring up a selection listis just one example of a mechanism for providing the input through theuser interface. Other alternative mechanisms will be readily apparent tothose skilled in the art.

Next the method includes updating or initiating (1904) a search based ona signature and/or other information of the contents of the selectedbounding box. Returning to the example of FIG. 18A or 18B, updating orinitiating of a search in that example follows from one of theselectable options being clicked on to cause the computer terminal 104(FIG. 1) to send a request to the server system 108 for a search of thestored video within the storage 190 to find anyone that may be likely tomatch the person within the bounding box 1810 (or the bounding box1860). Of course it will be understood that searches are not limited tojust searching for people. For instance, in some examples, instead oflooking for a person the search could be for a car or other motorizedvehicle. One might want to search for a car (or other motorized vehicle)if it has disappeared and searching video from various cameras in thevicinity of where the car may have travelled may reveal informationabout who may have the car or where the car may have been taken to.

Next the method includes generating or re-computing (1906) the matchlikelihoods. It will be appreciated that match likelihoods change as asearch is updated or newly run. This is because the system processingthe information that the contents of the bounding box 1810 (or thebounding box 1860) are a match impacts values of inputs to computationalformulas used by the analytics engine module 172 to assign likelihoodsof matches with respect to persons in other frames of other videos.

Finally the method includes updating or populating (1908) the userinterface based on the results of the search. For example, as hasalready been herein extensively described, image thumbnails, which arevisually representative of portions of potentially relevant videorecordings, can be dynamically presented on a user interface screen. Inthe case of an initial search, an empty portion of a user interfacescreen can become filled up with thumbnails that the search determinedto be potentially relevant. In the case of an updated search, thumbnailspresented on a portion of a user interface screen at a pre-search pointin time can become rearranged within the user interface and/or a numberof such thumbnails can be caused to be replaced with other thumbnailsbased on the search results.

Reference will now be made to FIG. 20 which is a screen shot of anotherexample user interface page 2002, which can be interacted with foridentifying same individuals or objects in video recordings inaccordance with another example embodiment. Similar to previouslydescribed user interface page 1702 (FIG. 17), the user interface page2002 is divided into three functional regions: a first UI region 2010, asecond UI region 2012 and a third UI region 2014. Within the first UIregion 2010, slider tool 2078 functions in a manner similar to theslider tool 1078 previously discussed in connection with FIG. 11, andthus the slider tool 2078 allows a person interacting with the userinterface page 2002 to set a filtering threshold as to which thumbnailsare permitted to appear on the user interface page 2002. Each of thethumbnails 2016 with the user interface page 2002 are organizedaccording to which of the video cameras 169 (FIG. 1) that are identifiedas haven taken the portions of the video recordings corresponding to theillustrated thumbnails 2016. Thus, it will be seen that there are fourthumbnails available under camera “2nd Floor Exhibit Entrance”. Thereare seven thumbnails available under camera “2nd Floor Hallway”.Finally, there are four thumbnails available under camera “2nd FloorCirculation”. It is also noted that there are drop-down selectors 2018and 2019 provided within the first UI region 2010. The drop-downselector 2018 impacts how the thumbnails 2016 are organized. As has beenpreviously discussed, organization by some parameter other than specificvideo camera is possible. The drop-down selector 2019 is labelled“Options” and allows the computer terminal user, once clicked on, topick other search-related option such as, for example, initiate anexport of all starred results or bookmark all the starred results. Theseoptions have already been herein discussed.

It will be noted that each of the thumbnails 2016 includes a squaregraphic 2020 in the upper left corner of the thumbnail and a stargraphic 2024 in the upper right corner of the thumbnail. These graphicsare superimposed over the images on the thumbnails 2016. The stargraphic 2024 can be clicked on to indicate that the object or person ofinterest is contained in the portion of the video recordingcorresponding to that thumbnail. When this occurs, the star graphic 2024may change from a light, translucent shading to a solid bright color (aswas previous described in connection with the user interface page 1702illustrated in FIG. 17). Thus, the search result corresponding to thethumbnail is starred. Alternatively the star graphic 2024 may change insome other manner when clicked on such as, for example, becomingcontinuously animated once selected to indicate the match. Regarding thesquare graphic 2020 in the upper left corner of each of the thumbnails2016, this can be clicked on to indicate that the object or person ofinterest is not contained in the portion of the video recordingcorresponding to that thumbnail. When this occurs, a red “X” may appearwithin the square graphic 1720 to provide visual indication of what hasoccurred. Also, those skilled in the art will appreciate that the red“X” is simply one of many possible design choices that can achieve thesame result of providing the desired indication of a non-match.

A video player 2025 is included in the second UI region 2012 within theuser interface page 2002. In the illustrated example, the video player2025 is playing a portion of the video recording not necessarilycorresponding to any of the thumbnails shown in the first UI region2010. The computer terminal user can watch the portion of the videorecording and, by watching this, the computer terminal user may see ornotice something that will allow a decision to be made as to whether ornot an individual or object of interest appears in the portion of thevideo recording so as to warrant updating or initiating a search for theindividual or object of interest (for example, in accordance with themethod 1900 shown and described in connection with FIG. 19). Inaccordance with at least one example embodiment, single clicking on anyof the thumbnails 2016 will bring the user to a starting point in theportion of the video corresponding to that thumbnail. By contract,double clicking on any of the thumbnails 2016 will bring the user to theexact point in the video as shown in the thumbnail image.

Within the illustrated example video player 2025, a bounding box 2029appears around a moving person within the displayed video. The boundingbox 2029 has the percentage “20%” shown just above the top of thebounding box to indicate to the computer terminal user that the personwithin the bounding box 2029 is calculated to have a 20% likelihood ofbeing the person of interest.

Within the third UI region 2014 is a two dimensional graph 2064. The twodimensional graph 2064 includes date and time along x-axis 2065. In theillustrated example, each thirty second interval is labelled starting at7:16.30 PM near the far left of the x-axis 2065 and ending at 7:21.00 PMat the far right of the x-axis 2065. In at least some examples, theinterval of time between the two ends of the x-axis 2065 can beincreased or decreased. For instance, the illustrated user interfacepage 2002 includes a slider tool 2034 similar to the slider tool 538described in connection with the user interface page 510 (FIG. 3).

The two dimensional graph 2064 also includes, along a y-axis 2067 of thegraph 2064, a listing of a plurality of camera identifications 2069 ofvideo cameras with respect to which a respective plurality of videorecordings of the video cameras are available for viewing. Each one ofthe plurality of camera identifications 2069 corresponds to a respectiveone of the plurality of video cameras 169 (FIG. 1) that is located in aunique known physical location with respect to all locations of theplurality of video cameras 169 of the surveillance system 100. Theorganization of the listing of the plurality of camera identifications2069 may be such that it is in descending order (from top to bottom)based those camera identification having the most markers. Alternativelyother forms of organization of the listing of the plurality of cameraidentifications 2069 are contemplated. In at least one alternativeexample, the listing of the plurality of camera identifications 2069 canbe made shorter by only showing those cameras having at least onestarred result.

Reference will now be made to FIG. 21 which is a screen shot of anotherexample user interface page 2102, which can be interacted with foridentifying same individuals or objects in video recordings inaccordance with another example embodiment. The user interface page 2102is similar to the user interface page 2002 (FIG. 20) and is divided intothree functional regions: a first UI region 2110, a second UI region2112 and a third UI region 2114, the general functions of which havebeen previously described. Each of the thumbnails 2116 with the userinterface page 2102 are organized into columns based on the timeinterval within which the portion of the video recording associated withthe thumbnail falls. A thumbnail 2118 has a cursor 2120 hovering over itcausing what is shown on the thumbnail 2118 to assume a different makeupas compared to one of the thumbnails 2116. Star icon 2122, when clickedon, allows the search result associated with the thumbnail 2118 to bestarred. Garbage can icon 2124, when clicked on, allows the thumbnail2118 to be marked as not of interest and removed from the first UIregion 2110. There is also superimposed text 2126 indicating a videorecord instance of time corresponding to thumbnail image.

Turning now to the third UI region 2114, illustrated is a twodimensional graph 2130. The two dimensional graph 2130 includes date andtime along x-axis 2131. In the illustrated example, the time intervallabelling is similar to the time interval labelling previously describedin connection with FIG. 17. Also, the interval of time between the twoends of the x-axis 2131 can be increased or decreased. For instance, theuser interface page 2102 includes a slider tool 2134, within the thirdUI region 2114, for this purpose.

The two dimensional graph 2130 also includes, along a y-axis 2135 of thegraph 2130, a listing of a plurality of camera identifications 2136 ofvideo cameras with respect to which a respective plurality of videorecordings of the video cameras are available for viewing. Each one ofthe plurality of camera identifications 2136 corresponds to a respectiveone of the plurality of video cameras 169 (FIG. 1) that is located in aunique known physical location with respect to all locations of theplurality of video cameras 169 of the surveillance system 100. Theorganization of the listing of the plurality of camera identifications2136 may be such that it is in descending order (from top to bottom)based those camera identification having the most markers. Alternativelyother forms of organization of the listing of the plurality of cameraidentifications 2136 are contemplated. In at least one alternativeexample, the listing of the plurality of camera identifications 2136 canbe made shorter by only showing those cameras having at least onestarred result.

Still with reference to the two dimensional graph 2130, there are twovertical (i.e. parallel to the y-axis 2135) lines 2137 and 2138. Thepositions of the lines 2137 and 2138 can be changed (for example,through use of the cursor 2120) to change the time range of the searchresults. By moving the line 2137 leftwards and/or the line 2138rightwards, the time range of the search results can be expanded.Conversely, by moving the line 2137 rightwards and/or the line 2138leftwards, the time range of the search results can be contracted.Having described the function of the vertical lines 2137 and 2138 inFIG. 21, it will be appreciated that similar vertical lines present insimilar UI regions of FIGS. 17 and 20 can, in at least some examples,function similarly.

Still with reference to the third UI region 2114, play button icon 2140is now described. Clicking the play button icon 2140 causes the starredvideo recording portions to be played back-to-back (i.e. the resultsassociated with the thumbnail icons 2197 and 2199). Also, on oppositesides of the play button icon 2140 are additional button icons 2142 and2143. Clicking on the button icon 2142 causes the playback speed of avideo recording portion to be slowed down. Clicking on the button icon2143 causes the playback speed of a video recording portion to be speedup.

With reference again to the first UI region 2110, drop-down selector2144 is labelled “Options” and serves the same function as the samelabelled selector shown in previously described FIGS. 17 and 20. Inaccordance with at least one example embodiment, “Export” can be one ofthe selections of the drop-down selector 2144 and by choosing it a newuser interface window 2202 (FIG. 22) is generated. Another drop-downselector 2145 is also shown within the first UI region 2110. Thedrop-down selector 2145 serves a similar function as the function of thedrop-down selector 1718 shown in FIG. 17.

Reference will now be made to FIG. 22 which is a screen shot of the userinterface page 2202 associated with an export function of theclient-side review application 144′ (FIG. 13). The user interface page2202 is divided into three functional regions: a first UI region 2210, asecond UI region 2112 and a third UI region 2214 (the general functionsof the second UI region 2212 have been previously described). Regardingthe first UI region 2210, within this region are three interface tools:interface tool 2213 for “Clip 1”, interface tool 2215 for “Clip 2” andinterface tool 2218 for additional settings associated with the Clips 1and 2. It will be understood that the Clips 1 and 2 correspond to thestarred results of FIG. 21 (i.e. results associated with the thumbnailicons 2197 and 2199, having associated markers 2151 and 2153 on the twodimensional graph 2130). Also, the interface tools 2213 and 2215 includeselectors to change the parameters of the video recording portions to beexported. For the illustrated example embodiment, any one or more of thefollowing can be changed: camera, start date and time of Clip (labelled“From:”), end date and time of Clip (labelled “To:”), and duration in“Days”, “Hours”, “Minutes” and “Seconds”.

Also within the first UI region 2210 are icons 2226 and 2228. The 2226and 2228 are labelled “Burn to Disc” and “Start Export” respectively”.By clicking on the icon 2226, the user can cause the back-to-backassembly of Clips 1 and 2 to be recorded onto a disc-type media (forexample, CD-R, HD DVD, Blu-ray Disc, etc.). By clicking on the icon2228, the user can cause the back-to-back assembly of Clips 1 and 2 tobe recorded onto a storage within the local system (for example, on ahard disk). In accordance with at least one alternative exampleembodiment, additional icons are contemplated such as, for instance, an“Export to Cloud” icon allowing the back-to-back assembly of Clips 1 and2 to be transmitted to (and stored in) a cloud storage.

In the third UI region 2214, there is a play button icon 2240. Clickingon the play button icon 2240 causes whatever is the currently selectedvideo recording portion to be played. Also, on opposite sides of theplay button icon 2240 are additional button icons 2242 and 2244.Clicking on the button icon 2242 causes playback speed of a videorecording portion to be slowed down. Clicking on the button icon 2244causes playback speed of a video recording portion to be speed up.

Certain adaptations and modifications of the described embodiments canbe made. For example, with respect to either the client-side videoreview application 144 (FIGS. 1 and 2) or the client-side video reviewapplication 144′ (FIG. 13), these have been herein described as packagedsoftware installed on the client terminal 104; however in somealternative example embodiments implementation of the UI can be achievedwith less installed software through the use of a web browserapplication (e.g. one of the other applications 152 shown in FIG. 1). Aweb browser application is a program used to view, download, upload,surf, and/or otherwise access documents (for example, web pages). Insome examples, the browser application may be the well-known Microsoft®Internet Explorer®. Of course other types of browser applications arealso equally possible including, for example, Google® Chrome™. Thebrowser application reads pages that are marked up (for example, inHTML). Also, the browser application interprets the marked up pages intowhat the user sees rendered as a web page. The browser application couldbe run on the computer terminal 104 to cooperate with softwarecomponents on the server system 108 in order to enable a computerterminal user to carry out actions related to providing input in orderto facilitate identifying same individuals or objects appearing in aplurality of different video recordings. In such circumstances, the userof the computer terminal 104 is provided with an alternative exampleuser interface through which the user inputs and receives information inrelation to the video recordings.

Although example embodiments have described a reference image for asearch as being taken from an image within recorded video, in someexample embodiments it may be possible to conduct a search based on ascanned photograph or still image taken by a digital camera. This may beparticularly true where the photo or other image is, for example, takenrecent enough such that the clothing and appearance is likely to be thesame as what may be found in the video recordings.

Therefore, the above discussed embodiments are considered to beillustrative and not restrictive, and the invention should be construedas limited only by the appended claims.

1. A method carried out in a surveillance system that includes at leastone storage and a plurality of video cameras, the method comprising:capturing, using the plurality of video cameras, a plurality of videorecordings; storing, in the at least one storage, the plurality of videorecordings that collectively include a plurality of video portionswithin which objects appear, wherein each of the video portions has arespective likelihood that an individual of interest appears therein;determining that each of the likelihoods in respect of a first number ofthe plurality of video portions exceed a likelihood of appearancethreshold, wherein the first number is less than all of the plurality ofvideo portions; and exporting the first number of the plurality of videoportions, the exporting including back-to-back assembly of the firstnumber of the plurality of video portions and subsequent storage thereofon another storage different than the at least one storage.
 2. Themethod as claimed in claim 1 further comprising determining that each ofthe likelihoods in respect of a second number of the plurality of videoportions are below the likelihood of appearance threshold.
 3. The methodas claimed in claim 2 wherein the first number of the plurality of videoportions correspond to starred results and the second number of theplurality of video portions correspond to results that have not beenstarred.
 4. The method as claimed in claim 1 wherein the likelihoods forthe first number of the plurality of video portions are percentagelikelihoods.
 5. The method as claimed in claim 4 wherein the likelihoodsfor the first number of the plurality of video portions are each onehundred percent.
 6. The method as claimed in claim 1 wherein the anotherstorage comprises a hard disk on a computer terminal.
 7. The method asclaimed in claim 1 wherein the another storage comprises cloud storage.8. The method as claimed in claim 1 further comprising providing aplurality of interface tools within a user interface page, and whereinthe exporting is carried out after the providing of the interface tools.9. The method as claimed in claim 8 wherein at least one of theinterface tool allows adjustments of start and end times of the videoportions being exported.
 10. A surveillance system comprising: aplurality of video cameras configured to capture a plurality of videorecordings; a server system configured to store the plurality of videorecordings that collectively include a plurality of video portionswithin which objects appear, wherein each of the video portions has arespective likelihood that an individual of interest appears therein;and at least one tangible, non-transitory, computer-readable storagemedium having instructions encoded therein, wherein the instructions,when executed by at least one processor, cause a carrying out of amethod comprising: determining that each of the likelihoods in respectof a first number of the plurality of video portions exceed a likelihoodof appearance threshold, wherein the first number is less than all ofthe plurality of video portions; and exporting the first number of theplurality of video portions, the exporting including back-to-backassembly of the first number of the plurality of video portions andsubsequent storage thereof outside of the server system.
 11. Thesurveillance system as claimed in claim 10 wherein the method furtherincludes determining that each of the likelihoods in respect of a secondnumber of the plurality of video portions are below the likelihood ofappearance threshold.
 12. The surveillance system as claimed in claim 11wherein the first number of the plurality of video portions correspondto starred results and the second number of the plurality of videoportions correspond to results that have not been starred.
 13. Thesurveillance system as claimed in claim 10 wherein the likelihoods forthe first number of the plurality of video portions are percentagelikelihoods.
 14. The surveillance system as claimed in claim 13 whereinthe likelihoods for the first number of the plurality of video portionsare each one hundred percent.
 15. The surveillance system as claimed inclaim 10 wherein the method further includes providing a plurality ofinterface tools within a user interface page, and wherein the exportingis carried out after the providing of the interface tools.
 16. Thesurveillance system as claimed in claim 15 wherein at least one of theinterface tool allows adjustments of start and end times of the videoportions being exported.
 17. A method comprising: displaying a twodimensional graph having date and time along the x-axis and, along they-axis, a listing of a plurality of camera identifications of videocameras with respect to which a respective plurality of video recordingsof the video cameras are available for viewing, and the video recordingshaving portions within which there is an above-threshold likelihood ofappearance of an individual or object having been identified as being ofinterest; plotting, based on the plurality of camera identifications andtimes on the x-axis associated with the portions of the videorecordings, n image thumbnails on the two dimensional graph, where n isan integer greater than two, the n image thumbnails being visuallyrepresentative of the portions of the video recordings, and a first ofthe n thumbnails being shown earliest in time along the x-axis and then^(th) thumbnail being shown latest in time along the x-axis; allowingselection of at least one of the n image thumbnails to be removed fromthe two dimensional graph; removing the at least one of the n imagethumbnails from the two dimensional graph; and recording that theindividual or object is absent in the portion of the video recordingassociated with the removed thumbnail.
 18. The method of claim 17wherein the method is carried out by a computer terminal incommunication with a server system, and the recording is recording inmemory of the computer terminal.
 19. The method of claim 17 furthercomprising: allowing a range of date and time along the x-axis to beexpanded when user input requesting such is received; and shrinkingsizes of the n image thumbnails when the range is expanded.
 20. Themethod of claim 17 wherein the n image thumbnails include visual indiciaof likelihood of appearance of the individual or object.